1. Field
The present disclosure relates generally to a method and a system for detecting edge pixels in an image plane, when separating an image signal into a set of image planes.
2. Description of Related Art
Scanning and exporting color images to a network has started to become one of the standard features offered by digital multifunction devices. File size of a color image is an important factor while exporting color images. In addition to offering different resolutions, different compression schemes are being offered to reduce the file size of the color image that needs to be exported. One of the popular compression/file formats that are currently being offered is Mixed or Multiple Raster Content (MRC) representation. The MRC representation provides a way to achieve high image quality with small file size.
The MRC representation of documents is versatile. It provides the ability to represent color images and either color or monochrome text. The MRC representation enables the use of multiple “planes” for the purpose of representing the content of documents. The MRC representation is becoming increasingly important in the marketplace. It has been already established as the main color-fax standard. It is also offered as a selection in the Scan-to-Export feature, for example, in digital multifunction devices.
In a MRC representation, an image is represented by more than one image plane. The main advantage of the MRC representation of documents is to provide an efficient way to store, transmit, and manipulate large digital color documents. The method exploits the properties of the human vision system, where the ability to distinguish small color variations is greatly reduced in the presence of high-contrast edges. The edge information is normally separated from the smoothly varying color information, and encoded (possibly at higher resolution than 1 bit per pixel) in one of the planes, called the Selector plane. The selector plane may have only one bit per pixel that controls the selection from either foreground or background. Following a careful separation, the various planes could be independently compressed using standard compression schemes (such as JPEG and G4) with good compression and high quality at the same time.
In digital image processing, an edge within an image is referred to a sharp change in local intensity or lightness. In other words, edges are features within an image that possess strong intensity contrast. Edges occur between distinct objects in a scene, or within textures and structure within an object. For instance, typographic characters on a white page background produce distinct edges. Edge pixels in a digital image are those pixels that occur at and about an edge in the image.
FIGS. 16 and 17 show a digital image (e.g., a bar chart) and an edge profile that is created from the digital image, respectively. As shown in FIG. 17, the black areas in the edge profile represent the edges within the digital image. The edge pixels are the pixels that occur at and about the edges (e.g., black areas in the edge profile as shown in FIG. 19) in the image.
In a three-layer segmentor, which is used for MRC representation, a minimum value and a maximum value for each pixel are calculated using a min/max module. The min/max module in the three-layer segmentor calculates the minimum value and the maximum value for each pixel based on a neighborhood window (e.g., an 8×8 neighborhood window) around that pixel (i.e., current pixel of interest). The min/max module in the three-layer segmentor may use a sliding window technique to determine the minimum value and the maximum value for each pixel. These minimum and maximum values are sometimes very different from the value of the current pixel of interest which may cause false detection of edges thus resulting in poor image quality and bigger file sizes.
The three-layer segmentor detects the edge pixels by comparing the minimum value or the maximum value of the pixels within the neighborhood window around the current pixel. The three-layer segmentor compares the current pixel value to determine the sign of the edges and then places the edges either in the background layer or the foreground layer which are further cleaned up in the later modules of the three-layer segmentor.
Also, the three-layer segmentor is configured to detect strong and weak edges in an image and to place dark valued edges in the foreground layer. The current three-layer segmentor sometimes detects false edges and hence creates large file sizes, for example, in photographic images. The current three-layer segmentor may also cause broken text in the low contrast text areas.
The present disclosure proposes a method that is configured to reduce false edge detection in all MRC models (i.e., currently existing models and any upcoming models). The method not only improves the text quality in the low contrast areas, but also improves the file sizes, for example, in photographic images. The method and the system for detecting edge pixels in an image plane described in the present disclosure can be extended to any MRC model, including, but not limited to a N layer MRC model, a 3+1 layer MRC model, a 3+N layer MRC model, or any other MRC models.